# set the default ggplot theme for the whole notebook
theme_set(theme_minimal())

# set defaults for the appearance/supression of code chunks in the markdown doc
knitr::opts_chunk$set(message = FALSE, echo = FALSE)

# set green to grey colour scale for use in tables and graphs
colour_palette <- scales::seq_gradient_pal(low = "palegreen4", high = "grey")
colour_scale <- colour_palette(seq(0, 1, length.out = 5))

# set the background colour for the table
background_colour <- "#EDEDED"

Framing

Audience:

Style:

The Friends of the Earth - “England’s Green Space Gap”

Friends of the Earth (FoE) have recently released a report focused on “England’s Green Space Gap.” The headline finding of the report is that one in five people in England live in areas where it is difficult to access green space . The report also provides a holistic overview of why green space is so important, by highlighting how individuals and communities benefit from having access to both public and private green space. These benefits which stretch far beyond the natural environmental itself, and encompass a myriad of social, health and economic benefits.

As part of the research underpinning the Green Space Gap report, Friends of the Earth have developed a new approach for classifying the extent to which neighborhoods (or Middle Super Output Areas in the terminology of the administrative geography) across England experience green space deprivation. Neighborhoods are classified into five groups; with group A including the least green space deprived neighborhoods, and E including the most green space deprived.

Friends of Earth have released the dataset that they developed and used to classify green space deprivation within the Green Space Gap report. In this notebook I plan to conduct an exploratory data analysis using this Friends of the Earth dataset. Before doing so, I think it might be helpful to outline the way in which Friends of the Earth processed the dataset. This is outlined in the figure below and incorporated the following steps:

Producing the Friends of the Earth Green Space Deprivation ratings.

n.b. In the report, Friends of the Earth draw on the Index of Multiple Deprivation (IMD) dataset to explore the relationship between the green space deprivation ratings and demographic factors including ethnicity and income.

The Structure of this Exploratory Data Analysis

Reading the Green Space Gap report and exploring the associated dataset, I was struck by a number of questions about the nature and scope of green space deprivation in England. I thought that these questions might be a good basis for my exploratory data analysis.

Below I address each of these questions in turn with the aim of extending upon the analysis of the data presented in the report. By doing so, I hope to contribute to the wider debate on maintaining and extending access to green space during the post-covid recovery.

Datasets Used

Ahead of moving on to the exploratory data analysis itself, I thought it would be helpful to very briefly document the datasets I used. This includes the Friends of the Earth dataset, and additional datasets from ONS which proved interesting or helpful in the context of my exploratory data analysis. In particular, I thought it was recording the versions of the dataset used where multiple version are available from the ONS

variable_name file_name notes url
green_space (FOE) Green Space Consolidated Data - England - Version 2.1.xlsx … https://friendsoftheearth.uk/nature/green-space-consolidated-data-england
LAD_to_region Local_Authority_District_to_Region__December_2019__Lookup_in_England.csv used the December 2019 version https://geoportal.statistics.gov.uk/datasets/3ba3daf9278f47daba0f561889c3521a_0
urban_rural_classification RUC_MSOA_2001_EW_LU.csv 2001 was the latest version available https://geoportal.statistics.gov.uk/datasets/rural-urban-classification-2001-of-msoas-in-england-and-wales

Ahead of conducting the exploratory data analysis I imported the three datasets and then merged into the single dataframe shown below.

What is the scale of the green space deprivation problem in England?

Green Space Deprivation in England
Understanding the scale of the problem
Green Space
Deprivation
Rating		 Neighbourhoods Population
Number % Millions of people %
Urgent action needed to improve access to green space
E 1108 16 9.62 18
D 955 14 8.21 15
Total 2,063 30 17.84 33
Action needed to protect access to green space
C 1727 25 13.54 25
B 1360 20 10.77 20
A 1641 24 12.58 23
Total 4,728 70 36.89 67
Source: Friends of the Earth

Below I plot the proportions of the r sum(msoa_by_rating$n_msoa) MSOAs analyzed given each green space deprivation rating.

Is green space deprivation an urban problem?

How is green space deprivation distributed across regions in England?

What can the dataset tell us about what green space deprivation looks like in England?

Summary / Conclusions

Further work

The distribution of green space deprivation ratings across England

Green space area per capita

dealing with outliers Boxplot shows outliers at 1.5*IQR + Q3 - they are part of the natural variability of the population, so it seems appropriate to retain the outliers, but zoom on the graphs because the .

not sure on whether or not to filter out outliers

So, I wondered if the outliers/very long tail are a result of areas with small populations and/very large areas of green space.

So, it looks like the it is the green space area has much more influence on green space area per capita, than population.

So, lets look at the distribution of green_space_area itself. This is relatively tricky given the wide range of values (as shown in the summary stats). I tried histograms and density plots too, but a box plot seemed the best way to understand the distribution. The first boxplot shows the full distribution and as a result is very difficult to interpret as the large outliers to the right of plot result in the box itself appearing as a single line and hence being very difficult to interpret. In the second plot hte x axis is cropped so it is straight forward to interpret the box component of the plot. However, this comes at the cost of failing to show the very large outliers within the distribution.

The extreme skew of the distribution can be seen in the summary statistics below. The median for green_space_area is 152,418 m2 while the maximum 636,087,671 m2.

A similarly extreme right skewed distribution can seen for green_space_area_per_capita, as shown in the plots and summary stats below. It is worth noting just how atypical many of the larger outliers are. The median for green_space_area_per_capita is less than 20 m2 per capita, while the maximum is approximately 100,000 m2 per capita.

So, I thought it was worth a quick look at the population density across English MSOAs. The first graph shows the kernel density function for the population density of English MSOAs. Key features of the distribution include:

The second plot groups MSOAs by their FoE green space deprivation rating and highlights:

Plotting population density against green space area and green space area per capita produces very associations. Note the log scales on both the x and y axis in both cases.

Green space access

Garden space

Urban-rural classification and green space deprivation ratings

Rural-urban classification at LA scale

https://www.gov.uk/government/statistics/local-authority-rural-urban-classification Rural-Urban Classification of Local Authorities Post-2009 Boundaries

Rural-urban classication at MSOA scale

https://geoportal.statistics.gov.uk/datasets/rural-urban-classification-2001-of-msoas-in-england-and-wales urban_rural_classification

Some thoughts on where I am in understanding the FoE ratings and green_space_area:

An alternative appraoch - clustering

https://community.alteryx.com/t5/Alteryx-Designer-Knowledge-Base/Standardization-in-Cluster-Analysis/ta-p/302296

My initial efforts in transforming the data - a log transformation and then scaling values to the unit interval (i.e. 0…1) - proved rather unsuccessful. See the summary stats below, with the transformed values remaining tightly grouped together around the median.

So, I wondered about focusing on a subset of the data which could be easier to work with. Perhaps given the focus on green space deprivation it makes sense to remove those clearly green space affluent MSOAs (e.g. those with 10,000’s m2 public green space per capita)

The distribution of green space deprivation ratings across the regions

The two plots below, respectively show for each region the numbers or proportion of MSOA with each green space deprivation rating. Key insights from the two plots include:

  • Over 45% of London’s MSOAs have been given the lowest rating (E). A further approximately 30% of London’s MSOAs are rated are rated D;
  • In the other regions (excluding London), the proportion of MSOAs with the lowest rating (E) in each is in the range of approximately 5-15%. The demonstrates that green space deprivation is a nationwide issue, that is perhaps unsurprisingly prominent in London (the largest city)
  • The North-East and the North-West have very similar distributions of MSOA green space deprivation ratings. With the a fairly symetrical and bell shaped distribution, centred on the C rating. Perhap reflecting a mix
  • The East of England, the South East and the South West have similar distribution, where the most commonly occurring rating is A.
  • Overall, there are considerable inequities within each region in terms of access to green space. All regions include a mix of green space deprived and affluent neighbourhoods.

Below I plot again plot the proportion of MSOAs within each region receiving each green space deprivation rating. This time faceting the plot by green space deprivation rating rather than region. This makes it easier to compare across regions at a given rating.

  • So we can clearly see the South East and Southwest have higher proportions of A rated MSOAs than say the North East and North West.
  • While outside of London, within each region there are similar proportion of neighbourhoods receiving the two highest green space deprivation ratings (D and E).

It would be easier to read if I produced separate plots for each green space deprivation rating, as then the regions could be put in rank order.

Next I explored an alternative appraoch to considering the distribution of msoas by rating and region. I plotted the proportion of MSOAs that received a specific rating by region. In order to address the ordering issue above, I produced one plot for each green space rating. This meant addressing the challenge of how to ensure the colour associated with a given region was applied consistently across the five plots. Here is where I found the an approach to doing this, using scale_…_manual.

How to map a colour to a value of a categorical variable …

This approach help me identify some additional insights:

  • For the highest green space deprivation ratings (D and E), the ranking of regions is the same: (1) London, (2) North West, (3) South East, (4) Yorkshire and the Humber and (5) West Midlands.
  • Over half of MSOAs given the highest green space deprivation rating are accounted for by just two regions: (1) London and (2) the North West.

Could do ridgeline plots for each region - for prop rated A and proportion rated E

The geographic distribution of green space deprivation ratings

https://datacarpentry.org/r-raster-vector-geospatial/06-vector-open-shapefile-in-r/

A quick visual inspection of the MSOAs colored by their green space deprivation rating, shows a similiar patter across the regions (with the exception of London). With the the D and E ratings (oranges and reds) occurring in smaller (presumably more densely populated MSOAs) which make up urban areas. While the larger, more rural MSOAs tend to be less green space deprived, and have A or B ratings. Given the whole region of London would probably be considered a continuous urban space, it is unsurprising to observe many green space deprived MSOAs across the region/plot, with relatively few less green space deprived areas present.

Ethnicity and green space deprivation

Wealth and green space deprivation

Health and green space deprivation

Covid and green space deprivation

Archived code

Ideas:

Russo, Alessio, and Giuseppe Cirella. 2018. “Modern Compact Cities: How Much Greenery Do We Need?” International Journal of Environmental Research and Public Health 15 (10): 2180. https://doi.org/10.3390/ijerph15102180.